Edge Computing and Digital Twin Based Smart Manufacturing

Protner, Jernej; Pipan, Miha; Zupan, Hugo; Resman, Matevž; Šimić, Marko; Herakovič, Niko

doi:10.1016/j.ifacol.2021.08.098

Cited by 8 publications

(2 citation statements)

References 26 publications

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“…Meanwhile, digital twin could also help with the maintenance, overhauls, and repairs of complex systems, products, and equipment [110][111][112]. Moreover, for optimization in resource allocation, digital twin can complement edge computing, improve efficiency, and reduce wastage [113,114]. Various digital twin infrastructures could be explored to support different phases in sustainable intelligent transformation with the integration of deep learning, machine learning, and artificial intelligence.…”

Section: Keyword Analysismentioning

confidence: 99%

A Bibliometric Analysis of Digital Twin in the Supply Chain

Lam,

Lee

2023

Mathematics

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Digital twin is the digital representation of an entity, and it drives Industry 4.0. This paper presents a bibliometric analysis of digital twin in the supply chain to help researchers, industry practitioners, and academics to understand the trend, development, and focus of the areas of digital twin in the supply chain. This paper found several key clusters of research, including the designing of a digital twin model, integration of a digital twin model, application of digital twin in quality control, and digital twin in digitalization. In the embryonic stage of research, digital twin was tested in the production line with limited optimization. In the development stage, the importance of digital twin in Industry 4.0 was observed, as big data, machine learning, Industrial Internet of Things, blockchain, edge computing, and cloud-based systems complemented digital twin models. Digital twin was applied to improve sustainability in manufacturing and production logistics. In the current prosperity stage with high annual publications, the recent trends of this topic focus on the integration of deep learning, data models, and artificial intelligence for digitalization. This bibliometric analysis also found that the COVID-19 pandemic drove the start of the prosperity stage of digital twin research in the supply chain. Researchers in this field are slowly moving towards applying digital twin for human-centric systems and mass personalization to prepare to transit to Industry 5.0.

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Section: Keyword Analysismentioning

confidence: 99%

A Bibliometric Analysis of Digital Twin in the Supply Chain

Lam,

Lee

2023

Mathematics

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“…The semantic DT model, along with microservices, can simplify the orchestration of various IoT devices and applications. In [122], the concept of edge computing based smart manufacturing with distributed control structure is demonstrated. The physical entities act as edge devices, the concepts of holons and digital agents are combined with local DTs to achieve local control, decision making, and optimization.…”

Section: B Iotmentioning

confidence: 99%

Survey on Digital Twin Edge Networks (DITEN) Toward 6G

Tang

Chen

Rodrigues

et al. 2022

IEEE Open J. Commun. Soc.

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The next generation (6G) wireless systems aim to cater to the Internet of Everything (IoE) and revolutionize customer services and applications to a fully intelligent and autonomous system. To achieve this, the digital twin edge network (DITEN) is proposed to combine mobile/multi-access edge computing (MEC) and digital twin (DT), thereby improving the network performance such as throughput and security, and reducing the cost of communication, computation, and caching. In DITENs, the network status can be continuously monitored, and based on the obtained network states, the networking schemes, such as routing and resource management, can be studied in the established DITENs from a centralized perspective. In this survey, we present a comprehensive overview of DITEN for 6G. First, we present the fundamental aspects of DITEN, including concept, framework, and potential. Second, a comprehensive design of DITEN is devised, including the DT modeling/updating, DT deployment, key issues, and enabling technologies. Then, the typical applications of DITEN towards 6G are provided, including the Internet of Things (IoT), vehicular network, spaceair-groud integrated network (SAGIN), healthcare, wireless systems, and other applications, along with the design of DITEN in each application, such as DT modeling, DT association, incentive mechanisms, and so on. Finally, challenges and open issues are discussed.

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